Game of Streams: How to Tame and Get the Most from Your Messaging Platforms
summary
Builds a three-service pipeline (source → processor → sink) using Spring Cloud Stream with both RabbitMQ and Apache Kafka binders; source polls a Raspberry Pi feed of live aircraft positions, processor maps Aircraft → EssentialAircraft via a reactive Flux and Java Supplier/Function/Consumer patterns, and sink logs results. Demonstrates consumer groups, auto-add partitions, server.port=0 for dynamic ports, and a Rabbit scalability claim (≈3× daily messaging volume of major IM/SMS). Code runs end-to-end but a manufacturer-mapping bug remains.
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chapters (12)
- 0:00Start
- 2:41Mark Heckler
- 5:40About Myself
- 8:31Why Use Messaging Platforms
- 17:51Examples
- 19:37What Is Spring Cloud Stream
- 21:42Spring Cloud Stream Is Built on Spring Boot
- 29:10Spring Initializer
- 31:52Actuator
- 32:38Spring Cloud Stream
- 41:09The Default Binder
- 54:52Resources
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